A field epidemiological investigation and emergency response of a confirmed COVID-19 case of a foreign airline cargo service personnel in Shanghai's international airport

Objective: To conduct on-site epidemiological investigation, emergency response, tracing of infection source and analysis of a confirmed COVID-19 case of a foreign airline cargo service staff member in Shanghai's international airport, aiming to provide reference for prevention of imported COVID-19 cases under regular prevention and control of COVID-19.

Impact of COVID-19 control measures on the spread of influenza

Objective: To analyze the effects of respiratory control measures before and after COVID-19 epidemic on influenza virus.

Promoting the capacity of control and prevention of emerging and imported infectious diseases: a practice in the integration of clinical and preventive medicine in Shanghai

Shanghai is a super-large metropolis with a highly developed globalization. Since the 21st century, Shanghai has experienced several threats of emerging and imported infectious diseases. Infectious disease surveillance has been established and developed from single-disease surveillances to a comprehensive surveillance network. Integration of clinical and preventive medicine has been gradually extended, which facilitates the improvement in the monitoring and early warning system. In 2020, when the COVID-19 epidemic spread, Shanghai quickly established a prevention and control expert team and a clinical medical expert team to effectively and shortly control local COVID-19 epidemic. In order to improve Shanghai's capacity to respond to major epidemics of infectious diseases and public health emergencies, the metropolis will build and improve a three-level diagnosis and treatment system for emerging, imported, rare, and unknown infectious diseases in the next five years. Based on the big data monitoring platform of medical institutions, Shanghai will achieve the intelligence-supported diagnosis and treatment of infectious diseases, and consolidate the cooperation to implement the integration of clinical and preventive medicine.

Establishing a modernized and integrated surveillance system for infectious diseases in a megacity with model transformation and innovation

The COVID-19 epidemic fully reflects the importance of surveillance and early warning of infectious diseases, and also puts forward higher requirements for us to further improve epidemic surveillance to achieve early detection, early identification, early reporting and early disposal of various pathogens. In this paper, we reviewed the development of the integrated surveillance system for infectious diseases in Shanghai in recent years, illustrated the approach of integrated surveillance based on syndromes and events, and initially summarized the key results of the integrated surveillance, expanding the scope of surveillance, improving sensitivity and enhancing the capacity of the system. Moreover, considering the requirements regarding the public health system, we provide some thoughts and suggestions on further expanding of the integrated surveillance, continuously strengthening the integration of public health surveillance with clinical diagnosis and treatment, laboratory capacity development, and public health information technology.

Deep convolutional neural networks for construction and demolition waste classification: VGGNet structures, cyclical learning rate, and knowledge transfer.

The sorting of Construction and Demolition (C&D) waste is a critical step to linking the recycling system and to the macro prediction, which helps to promote the development of the circular economy. Moreover, the effective classification and automated separation process will also help to stop the spreading of pathogenic organisms, such as virus and bacteria, by minimizing human intervention in the sorting process, while also helping to prevent further contamination by COVID-19 virus. This study aims to develop an efficient method to sort C&D waste through deep learning combined with knowledge transfer approach. In this paper, CVGGNet models, that is four VGG structures (VGGNet-11, VGGNet-13, VGGNet-16, and VGGNet-19), based on knowledge transfer combined with the technology of data augmentation and cyclical learning rate, are proposed to classify ten types of C&D waste images. Results show that 2.5 × 10-4, 1.8 × 10-4, 0.8 × 10-4, and 1.0 × 10-4 are the optimum learning rate for CVGGNet-11, CVGGNet-13, CVGGNet-16, and CVGGNet-19, respectively. Knowledge transfer helped shorten the training time from 1039.45 s to 991.05 s, and while it improved the performance of the CVGGNet-11 model in training, validation, and test datasets. The average training time increases as the number of the layers in the CVGGNet architecture rises: CVGGNet-11 (991.05 s) ˂ CVGGNet-13 (1025.76 s) ˂ CVGGNet-16 (1090.48 s) ˂ CVGGNet-19 (1337.81 s). Compared to other CVGGNet models, CVGGNet-16 showed an excellent performance in various C&D waste types, in terms of accuracy (76.6%), weighted average precision (76.8%), weighted average recall (76.6%), weighted average F1-score (76.6%) and micro average ROC (87.0%). In addition, the t-distributed Stochastic Neighbor Embedding (t-SNE) approach can reduce the dataset to a lower dimension and distinctly separate each type of C&D waste. This study demonstrates the good performance of CVGGNet models that can be used to automatically sort most of the C&D waste, paving the way for better C&D waste management.

Assessment and prediction of the oversea imported risk of COVID-19 in Shanghai

Objective: To determine the association between global epidemic of COVID-19 and local situation of imported cases from abroad to Shanghai, and then to predict the risk of imported COVID-19 epidemic from December 2020 through March 2021.

Long-term immune responses in patients with confirmed novel coronavirus disease-2019: a 9-month prospective cohort study in Shanghai, China.

BACKGROUND: The duration of antibodies against SARS-CoV-2 in Covid-19 patients remains uncertain. Longitudinal serological studies are needed to prevent disease and transmission of the virus. METHODS: In 2020, 414 blood samples were tested, obtained from 157 confirmed Covid-19 patients, in a prospective cohort study in Shanghai. RESULTS: The seropositive rate of IgM peaked at 40.5% (17/42) within 1 month after illness onset and then declined. The seropositive rate of IgG was 90.6% (58/64) after 2 months, remained above 85% from 2 to 9 months and was 90.9% (40/44) after 9 months. Generalized estimating equations models suggested that IgM (P < 0.001) but not IgG significantly decreased over time. Age ≥ 40 years (adjusted odds ratio [aOR] 4.531; 95% confidence interval [CI] 1.879-10.932), and cigarette smoking (aOR 0.344; 95% CI 0.124-0.951) were associated with IgG, and age ≥ 40 years (aOR 2.820; 95% CI 1.579-5.036) was associated with IgM. After seroconversion, over 90% and 75.1% of subjects were estimated to remain IgG-positive 220 and 254 days, respectively. Of 1420 self-reported symptoms questionnaires, only 5% reported symptoms 9 months after onset. CONCLUSIONS: In patients with a history of natural infection, anti-SARS-CoV-2 IgG is long-lived, being present for at least 9 months after illness onset. The long duration of natural immunity can mitigate and eliminate Covid-19 and the ongoing pandemic.

Changes in obesity and lifestyle behaviours during the COVID-19 pandemic in Chinese adolescents: A longitudinal analysis from 2019 to 2020.

BACKGROUND: Since December 2019, the coronavirus disease 2019 (COVID-19) has become a global pandemic. Currently, the COVID-19 pandemic is still ongoing. What changes have taken place in the obesity and obesity-related lifestyle behaviours of adolescents during the first year of the COVID-19 pandemic? OBJECTIVE: This study aims at analysing the changes in obesity and lifestyle behaviours of Chinese adolescents before and 1 year after the outbreak of the COVID-19 pandemic, providing evidence for the global strategies to respond to the impact of the COVID-19 pandemic on adolescent obesity. METHODS: Physical examinations and student health and influencing factors questionnaires were conducted among 6047 adolescents aged 11-16 years by health professionals in Shanghai, China, before the COVID-19 pandemic (September-November of 2019) and 1 year after the outbreak of the COVID-19 pandemic (September-November of 2020). Paired χ2 tests, paired t-tests or Wilcoxon signed-rank test was used to evaluate the changes in the obesity prevalence, BMI and lifestyle behaviours from 2019 to 2020. RESULTS: 1 year after the outbreak of the COVID-19 pandemic, the obesity prevalence of Chinese adolescents rose from 14.2% to 15.4% (p < 0.01), mainly because of the increase in boys. And the average BMI increased from 20.3 to 21.2 kg/m2 (p < 0.01). Their lifestyle behaviours have also significantly changed. The mobile screen time increased from 0.25-1.50 h/day to 0.33-2.00 h/day (p < 0.01). The proportion of adolescents who participated in MVPA for ≥60 min/day on all 7 days during the past week dropped from 14.4% to 11.7% (p < 0.01). The generalized estimation equation analysis indicated that adolescents who participated in MVPA for ≥60 min/day on all 7 days had a lower likelihood of having obesity. Boys with computer time ≥2 h/day and girls with mobile screen time ≥2 h/day or TV time ≥2 h/day had a higher likelihood of having obesity. CONCLUSION: This study found that 1 year after the outbreak of the COVID-19 pandemic, the BMI and obesity prevalence of Chinese adolescents increased and obesity-related lifestyle behaviours have also changed.

Dynamic communicable disease risk assessment during the third China international import expo in Shanghai

Objective: To identify and assess the potential communicable disease risk during the Third China International Import Expo (CIIE) in Shanghai in 2020 and provide evidence and suggestions for the emergency preparedness and response.

Epidemiological and co-infection characteristics of common human coronaviruses in Shanghai, 2015-2020: a retrospective observational study.

The coronavirus disease (COVID-19) pandemic is a major challenge worldwide. However, the epidemic potential of common human coronaviruses (HCoVs) remains unclear. This study aimed to determine the epidemiological and co-infection characteristics of common HCoVs in individuals with influenza-like illness (ILI) and severe acute respiratory infection (SARI). This retrospective, observational, multicentre study used data collected from patients admitted to nine sentinel hospitals with ILI and SARI from January 2015 through December 2020 in Shanghai, China. We prospectively tested patients for a total of 22 respiratory pathogens using multi-real-time polymerase chain reaction. Of the 4541 patients tested, 40.37% (1833/4541) tested positive for respiratory pathogens and 3.59% (163/4541) tested positive for common HCoVs. HCoV infection was more common in the non-endemic season for respiratory pathogens (odds ratio: 2.33, 95% confidence interval: 1.64-3.31). HCoV-OC43 (41.72%, 68/163) was the most common type of HCoV detected. The co-infection rate was 31.29% (51/163) among 163 HCoV-positive cases, with HCoV-229E (53.13%, 17/32), the HCoV type that was most frequently associated with co-infection. Respiratory pathogens responsible for co-infections with HCoVs included parainfluenza virus, rhinovirus/enterovirus, influenza A virus, and adenovirus. Furthermore, we identified one patient co-infected with HCoV-OC43 and HCoV-NL63/HKU1. The prevalence of common HCoVs remains low in ILI/SARI cases, in Shanghai. However, the seasonal pattern of HCoVs may be opposite to that of other respiratory pathogens. Moreover, HCoVs are likely to co-exist with specific respiratory pathogens. The potential role of co-infections with HCoVs and other pathogenic microorganisms in infection and pathogenesis of ILI and SARI warrants further study.

Epidemiological and clinical characteristics of 161 discharged cases with coronavirus disease 2019 in Shanghai, China.

BACKGROUND: In December 2019, the outbreak of coronavirus disease 2019 (COVID-19) began in Wuhan, China, and rapidly spread to other regions. We aimed to further describe the epidemiological and clinical characteristics of discharged COVID-19 cases and evaluate the public health interventions. METHODS: We collected epidemiological and clinical data of all discharged COVID-19 cases as of 17 February 2020 in Shanghai. The key epidemiological distributions were estimated and outcomes were also compared between patients whose illness were before 24 January and those whose illness were after 24 January. RESULTS: Of 161 discharged COVID-19 cases, the median age was 45 years, and 80 (49.7%) cases were male. All of the cases were categorized as clinical moderate type. The most common initial symptoms were fever (85.7%), cough (41.0%), fatigue (19.3%), muscle ache (17.4%), sputum production (14.9%), and there were six asymptomatic cases. 39 (24.2%) cases got infected in Shanghai, and three of them were second-generation cases of Shanghai native cases. The estimated median of the time from onset to first medical visit, admission, disease confirmation, and discharge for 161 cases was 1.0 day (95% CI, 0.6-1.2), 2.0 days (95% CI, 1.5-2.6), 5.2 days (95% CI, 4.6-5.7), 18.1 days (95% CI, 17.4-18.8), respectively. The estimated median of the time from admission to discharge was 14.0 days (95% CI, 13.3-14.6). The time from onset to first medical visit, admission and disease confirmation were all shortened after the Shanghai's first-level public health emergency response. In Cox regression model, the significant independent covariates for the duration of hospitalization were age, the time from onset to admission and the first-level public health emergency response. CONCLUSIONS: Local transmission had occurred in Shanghai in late January 2020. The estimated median of the time from onset to discharge of moderate COVID-19 was 18.1 days in Shanghai. Time intervals from onset to first medical visit, admission and disease confirmation were all shortened after the Shanghai's first-level public health emergency response. Age, the first-level public health emergency response and the time from onset to admission were the impact factors for the duration of hospitalization.

Three infection clusters related with potential pre-symptomatic transmission of coronavirus disease (COVID-19), Shanghai, China, January to February 2020.

We report three clusters related with potential pre-symptomatic transmission of coronavirus disease (COVID-19) between January and February 2020 in Shanghai, China. Investigators interviewed suspected COVID-19 cases to collect epidemiological information, including demographic characteristics, illness onset, hospital visits, close contacts, activities' trajectories between 14 days before illness onset and isolation, and exposure histories. Respiratory specimens of suspected cases were collected and tested for SARS-CoV-2 by real-time reverse-transcriptase polymerase chain reaction (rRT-PCR) assay. The interval between the onset of illness in the primary case and the last contact of the secondary case with the primary case in our report was 1 to 7 days. In Cluster 1 (five cases), illness onset in the five secondary cases was 2 to 5 days after the last contact with the primary case. In Cluster 2 (five cases) and Cluster 3 (four cases), the illness onset in secondary cases occurred prior to or on the same day as the onset in the primary cases. The study provides empirical evidence for transmission of COVID-19 during the incubation period and indicates that pre-symptomatic person-to-person transmission can occur following sufficient exposure to confirmed COVID-19 cases. The potential pre-symptomatic person-to-person transmission puts forward higher requirements for prevention and control measures.

Clusters of 2019 coronavirus disease (COVID-19) cases in Chinese tour groups.

International travel may facilitate the spread of the novel coronavirus disease (COVID-19). The study describes clusters of COVID-19 cases within Chinese tour groups travelling in Europe January 16-28. We compared characteristics of cases and non-cases to determine transmission dynamics. The index case travelled from Wuhan, China, to Europe on 16 January 2020, and to Shanghai, China, on 27 January 2020, within a tour group (group A). Tour groups with the same outbound flight (group B) or the same tourism venue (group D) and all Chinese passengers on the inbound flight (group C) were investigated. The outbreak involved 11 confirmed cases, 10 suspected cases and six tourists who remained healthy. Group A, involving seven confirmed cases and six suspected cases, consisted of familial transmission followed by propagative transmission. There was less pathogenicity with propagative transmission than with familial transmission. Disease was transmitted in shared outbound flights, shopping venues within Europe and inbound flight back to China. The novel coronavirus caused clustered cases of COVID-19 in tour groups. When tourism and travel opens up, governments will need to improve screening at airports and consider increased surveillance of tour groups-particularly those with older tour members.

Pre-symptomatic transmission of novel coronavirus in community settings.

We used contact tracing to document how COVID-19 was transmitted across 5 generations involving 10 cases, starting with an individual who became ill on January 27. We calculated the incubation period of the cases as the interval between infection and development of symptoms. The median incubation period was 6.0 days (interquartile range, 3.5-9.5 days). The last two generations were infected in public places, 3 and 4 days prior to the onset of illness in their infectors. Both had certain underlying conditions and comorbidity. Further identification of how individuals transmit prior to being symptomatic will have important consequences.

Epidemiological and clinical characteristics of 333 confirmed cases with coronavirus disease 2019 in Shanghai, China.

Coronavirus disease 2019 (COVID-19) is an emerging infectious disease first identified in Wuhan City, Hubei Province, China. As of 19 February 2020, there had been 333 confirmed cases reported in Shanghai, China. This study elaborates on the epidemiological and clinical characteristics of COVID-19 based on a descriptive study of the 333 patients infected with COVID-19 in Shanghai for the purpose of probing into this new disease and providing reference. Among the 333 confirmed cases in Shanghai, 172 (51.7%) were males and 161 (48.3%) were females, with a median age of 50 years. 299 (89.8%) cases presented mild symptoms. 139 (41.7%) and 111 (33.3%) cases were infected in Wuhan and Shanghai, respectively. 148 (44.4%) cases once had contact with confirmed cases before onset, while 103 (30.9%) cases had never contacted confirmed cases but they had a sojourn history in Wuhan. The onset date of the first case in Shanghai was 28 December, with the peak appearing on 27 January. The median incubation period of COVID-19 was estimated to be 7.2 days. 207 (62.2%) cases had fever symptoms at the onset, whereas 273 (82.0%) cases experienced fever before hospitalization. 56 (18.6%) adults experienced a decrease in white blood cell and 84 (42.9%) had increased C-reactive protein after onset. Elderly, male and heart disease history were risk factors for severe or critical pneumonia. These findings suggest that most cases experienced fever symptoms and had mild pneumonia. Strengthening the health management of elderly men, especially those with underlying diseases, may help reduce the incidence of severe and critical pneumonia. Time intervals from onset to visit, hospitalization and diagnosis confirmed were all shortened after Shanghai's first-level public health emergency response. Shanghai's experience proves that COVID-19 can be controlled well in megacities.